ShadowNet: A Secure and Efficient On-device Model Inference System for Convolutional Neural Networks.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023
Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile Apps.
Proceedings of the 30th USENIX Security Symposium, 2021
ShadowNet: A Secure and Efficient System for On-device Model Inference.
CoRR, 2020
Mind Your Weight(s): A Large-scale Study on Insufficient Machine Learning Model Protection in Mobile Apps.
CoRR, 2020
OAT: Attesting Operation Integrity of Embedded Devices.
Proceedings of the 2020 IEEE Symposium on Security and Privacy, 2020
Dominance as a New Trusted Computing Primitive for the Internet of Things.
Proceedings of the 2019 IEEE Symposium on Security and Privacy, 2019
PTrix: Efficient Hardware-Assisted Fuzzing for COTS Binary.
Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security, 2019
OEI: Operation Execution Integrity for Embedded Devices.
CoRR, 2018
VButton: Practical Attestation of User-driven Operations in Mobile Apps.
Proceedings of the 16th Annual International Conference on Mobile Systems, 2018
Shreds: Fine-Grained Execution Units with Private Memory.
Proceedings of the IEEE Symposium on Security and Privacy, 2016